Runtime enforcement infrastructure for AI
Adopt AI
with confidence.
Continuous assessment, runtime enforcement, and auditable evidence for enterprise AI agents.
Your existing security stack wasn't built for autonomous agents.
01
You don't know what your agents are doing
Agents are deployed across the business faster than security can track them. You can't enforce what you can't see — and most enterprises can't see most of what's running.
02
Policies exist. Enforcement doesn't.
Policies exist in documents. Enforcement exists in hope. Agents operate outside sanctioned boundaries — undetected until an incident surfaces.
03
When an incident hits, you have nothing provable
When an incident occurs — or an auditor asks — you need tamper-evident proof that controls ran. Most organizations have logs. Logs aren't evidence.
Enforcement lifecycle
Discover
Spike
Interview-driven AI system inventory. Risk classification and security posture baseline for every AI system and agent in your environment.
Operate
Loop
Policy authoring, human-in-the-loop review, and approval workflows. Connect policy intent to deterministic, auditable enforcement rules.
Enforce
Steer
Runtime policy enforcement at the network layer. Every agent decision evaluated, steered, or blocked — at <14ms, without grounding your agents.
Evidence
Pulse · Steer
Tamper-evident audit chain at every enforcement decision. Regulatory tracking. Incident monitoring. Evidence packages ready when incidents occur or auditors ask.
From unquantified risk to governed AI capacity.
A working cycle for governing AI agents at enterprise scale — from system discovery to runtime enforcement to audit-ready evidence.
Today — the problem
Human workloads.
Unquantified risk.
01 · Assess
Spike
// discover · assess
Quantify AI risk. Classify regulatory obligation by risk tier and regulatory obligation.
Produces
System inventory · risk classification · gap analysis · remediation roadmap
02 · Operate
Loop
// operate
Author, review, and approve enforcement policies. Human-in-the-loop oversight.
Produces
Approved policies · policy decisions · workflow records
03 · Enforce
Steer
// enforce · evidence
Apply policies at runtime. Steer or block out-of-boundary behavior at <14ms.
Produces
Enforcement decisions · tamper-evident audit chain · behavioral telemetry
04 · Evidence
Pulse
// track · monitor
Monitor behavior, track regulatory change, package evidence for audit.
Produces
Audit packages · posture scores · regulatory obligation status
Confidence accumulates → unlock more AI capacity each cycle
With EnforceGrid
AI workloads.
Governed risk.
AI risk follows the same maturity path as other operational risks — quantified, controlled, and eventually insurable.
One platform. Four products.
Each solves a distinct phase of the AI enforcement lifecycle. Hover to explore.
// discover · assess
Spike
AI-powered AI risk assessment and regulatory gap analysis
AI agents interview your teams in parallel, classify risk by risk tier and regulatory obligation, and deliver gap analysis and draft documentation in 5–7 days — not months of consulting engagement.
// enforce · evidence
Steer
Runtime enforcement & audit for AI agents
One URL change. 23 managed policies covering OWASP, EU AI Act, and PCI DSS. Enforcement at <14ms overhead. Tamper-evident audit chain at every decision. Apache 2.0 Core.
// track · monitor
Pulse
Regulatory intelligence & incident tracking
Structured regulatory intelligence and incident tracking across jurisdictions. Tuned to EU AI Act, DORA, and emerging AI regulation globally.
// operate
Loop
Workspace for policies, evidence & governance ops
Policy authoring, evidence review, human-in-the-loop decision workflows, and compliance reporting — the operational layer for security and compliance teams who run AI programs at scale.
Built for the teams who secure and govern enterprise AI.
Deploys in an afternoon. Enforces at the network layer.
One URL change is all it takes. Steer sits at the network layer — no SDK to install, no agent framework dependency, no agent code to modify. Enforcement runs at <14ms p50 latency with zero payload exposure outside your network boundary.
≤14ms p50 enforcement overhead · zero SDK dependencies
- One URL change — no agent or framework code changes
- Fail-open by default — agents keep running if enforcement is unreachable
- Provider-agnostic — OpenAI, Anthropic, Gemini, Mistral, self-hosted models
- Apache 2.0 Core — run in your own VPC, audit the code, own the evidence
Deterministic enforcement, not best-effort detection.
Cedar-based policies make out-of-boundary agent behavior structurally impossible — not flagged after the fact, prevented at the network layer. Every enforcement decision generates a cryptographically chained record you can take to the board or the regulator. Your agents keep running. Your policy boundaries don't move.
23 managed policies · cryptographic chain · OWASP ASI01–10 covered
- Cryptographic audit chain at every enforcement decision
- OWASP Agentic AI ASI01–10 mapped out of the box
- NIST AI RMF, ISO 42001, GDPR Art. 22/25, PCI DSS coverage
- Insurance-grade evidence — artifacts, not just logs
Regulatory evidence before the auditor asks.
OWASP Agentic AI, NIST AI RMF, and EU AI Act all require runtime enforcement controls and documented evidence. Generate that evidence automatically — for every AI decision, at the network layer.
OWASP · NIST AI RMF · EU AI Act mapped · board-ready evidence
- Runtime-generated enforcement documentation — not retroactive reconstruction
- Board-ready posture score with breakdown by AI system and obligation
- Remediation roadmap mapped to Dec 2, 2027 (standalone) / Aug 2, 2028 (embedded) deadlines
- Evidence packages structured for conformity assessment
Deploy for clients in hours. Evidence included.
One Helm chart. One URL change. Running in any client environment — any cloud, any Kubernetes cluster, any LLM provider — in under an hour. Enforcement and tamper-evident audit chain live from day one. No client code changes required.
Provider-agnostic · self-hostable · Apache 2.0 Core
- One Helm chart — runs in any Kubernetes environment, any cloud
- Zero client code changes — enforcement sits at the network layer
- Compliance evidence artifacts generated automatically — bundle into your managed service
- Speak to us about partner pricing and white-label arrangements
Get started
Start with Steer. Available today.
One URL change. Running in under five minutes. No SDK to install, no deployment to coordinate.
Explore Steer →Open-source enforcement engine · Apache 2.0 Core · Self-hosted or managed cloud